The RVC, stationary-point-count method is modified from Bohnsack and Bannerot (1986) and is conducted on shallow (<100ft), hardbottom coral reef habitats. Field surveys use a one-stage design to sample 50 m x 50 m grid cells selected using a stratified-random sampling allocation. This data set represents sample locations in the Florida Keys. Only those strata types found within the MIR areas were considered (table 1).
A selection of fish species were chosen to represent different trophic levels and functional roles.
Density is represented as the number of individuals per 177 m^2.
Survey occurrence within MIR sites and outside.
Relative length frequency of species within MIR sites and outside.
MIR_LF(df = MIR_data, spp = "hae flav", bin_size = 5, yrs = 2022, spp_name = "French grunt")
MIR_LF(df = MIR_data, spp = "hae flav", bin_size = 5, yrs = 2024, spp_name = "French grunt")MIR_LF(df = MIR_data, spp = "spa viri", bin_size = 5, yrs = 2022, spp_name = "Stoplight parrotfish")
MIR_LF(df = MIR_data, spp = "spa viri", bin_size = 5, yrs = 2024, spp_name = "Stoplight parrotfish")MIR_LF(df = MIR_data, spp = "sca guac", bin_size = 5, yrs = 2022, spp_name = "Rainbow parrotfish")
MIR_LF(df = MIR_data, spp = "sca guac", bin_size = 5, yrs = 2024, spp_name = "Rainbow parrotfish")MIR_LF(df = MIR_data, spp = "ste plan", bin_size = 2, yrs = 2022, spp_name = "3-spot damselfish")
MIR_LF(df = MIR_data, spp = "ste plan", bin_size = 2, yrs = 2024, spp_name = "3-spot damselfish")MIR_data_copy <- MIR_data
MIR_data_copy$sample_data <- MIR_data_copy$sample_data %>%
mutate(SPECIES_CD = if_else(SPECIES_CD == "CAL CALA", "CAL NODO", SPECIES_CD))
#Merged CAL CALA and CAL NODO to graph both porgy species together
MIR_LF(df = MIR_data_copy, spp = "CAL NODO", bin_size = 2, yrs = 2022, spp_name = "Porgy")
MIR_LF(df = MIR_data_copy, spp = "CAL NODO", bin_size = 2, yrs = 2024, spp_name = "Porgy")A work by Jeremiah Blondeau + Rob Harper